What is OLAP: Online Analytics Processing
OLAP (online analytics processing) is a technology behind many business intelligence (BI) applications. It is a powerful technology for data discovery, including unlimited report viewing capabilities, complex analytical calculations, and predictive “if any” scenario (budget, forecast) planning.
How does OLAP work?
The data warehouse can extract information from various data sources and formats such as text files, excel sheets, multimedia files, etc. The extracted data has been cleared and replaced. The figure is calculated by the Online analytics processing server is the full information for further analysis.
Basic analytical operations of OLAP
There are four types of analytical work:
- Slice and dice
- Pivot (rotate)
The drill-down operation converts less detailed data into more detailed data through one of two methods – moving down the concept classification or adding a new dimension to the cube.
Roll up is the opposite of the drill-down function. This Online analytics processing collects the data of the cube by moving it evenly or by reducing the number of dimensions.
Slice and Dice:
The slice operation forms a sub-cube by selecting the same dimension from the central oval cube, for example, you can perform a piece by highlighting all the data for the first financial or calendar quarter (time direction) of the organization.
The pivot function rotates the existing cube view to represent a new representation of the data – activating the dynamic multidimensional view of the data. The Online analytics processing Pivot Function is comparable to the Pivot Table feature in spreadsheet software, such as Microsoft Excel.
Types of OLAP Systems
Online analytics processing systems are usually found in one of three types:
- Multidimensional (MOLAP) Olap is an index that is directly in a multidimensional database.
- Relational (ROLAP) is OLAP that performs dynamic multidimensional analysis of data stored in relative databases
- Hybrid (HOLAP) is a combination of ROLAP and MOLAP. HOLAP was developed to combine ROLAP’s maximum data capacity with high processing capability.
Advantages of OLAP
- It is a platform for all types of business including planning, budgeting, reporting, and analysis.
- The information and calculations in the Online analytics processing cube are constant. This is an important advantage.
- Quickly create and analyze “what if” scenarios
- Easily search the OLAP database for broad or specific terms.
- It provides building blocks for business modeling tools, data mining tools, performance reporting tools.
- Allows users to slice and dice cube data through different dimensions, steps, and filters.
- It is good for analyzing time series.
- With OLAP it’s easy to find some clutter and outsiders.
- It is a powerful scenario online analytics process system that provides fast response times
Disadvantages of OLAP
- It requires sorting the data into a star or snowflake schema. These schemes are complex to implement and manage
- You cannot have a large number of dimensions in a single OLAP cube
- Transactional data cannot accessed with the OLAP system.
- Any changes to the OLAP cube require a complete update cube. This is a time-consuming process
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